Understanding the Information Search Process within a Tourism Domain-specific Search Engine

Mitsche, Nicole

doi:10.1007/3-211-27283-6_17

Cited by 18 publications

(14 citation statements)

References 18 publications

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“…However, travel is a complex bundle of experiences with only a small set of tangible components. In order to make these intangible aspects tangible, the experiential aspects of tourism have to be translated into tangible attributes (Mitsche, 2005). Travelers learn about products prior to the actual purchase primarily to assess what consumption experience the product can offer and how well it can meet the expectations of the anticipated experience (Hoch & Deighton, 1989).…”

Section: Literature Reviewmentioning

confidence: 99%

Travelers' Intent to Use Mobile Technologies as a Function of Effort and Performance Expectancy

Lehto

Park

2009

Journal of Hospitality Marketing & Management

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Due to the nature of the tourism product (inherently experiential, intangible, and heterogeneous) and the substantial geographical distances, trial prior to the purchase decision is almost impossible. These kinds of distances could be overcome by information about the product, which is available in advance and can be gathered by the consumer. The upsurge of mobile technology is providing great flexibility for the tourism industry and travelers who have hierarchical needs for information beyond the extent or extension of alternative user-centered information channels and other support systems on the road. Current research of the use of mobile technology in tourism has focused on design and technological issues of mobile guides. Little research has been conducted to understand travelers' attitude and use patterns. This research aims to apply the key concepts of technology acceptance model (TAM) to understand how user experience, performance, and effort expectation interplay with user intention. Using structural equation modeling on online survey data, six hypotheses which describe the relationships between the variables of the model were S. Oh et al. tested. The results indicated that the proposed model could well predict the tourists' intentions toward mobile device usage for their next trip. Travelers' intentions to use mobile devices primarily depended on performance expectancy rather than effort expectancy. Previous information and communication technologies (ICT) usage and trip experience were positively related to the performance expectancy and effort expectancy, respectively. The indirect effects of previous ICT usage and previous trip experience on behavioral intention were further identified.

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Section: Literature Reviewmentioning

confidence: 99%

Travelers' Intent to Use Mobile Technologies as a Function of Effort and Performance Expectancy

Lehto

Park

2009

Journal of Hospitality Marketing & Management

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“…In quantifying tourists' online information search behavior, Ho and Liu () investigated the number of sites (URL) visited, number of webpages (screens) viewed, total search time, and number of webpages read within each site and so on. Mitsche () examined travel planners' search keywords within open text queries for a better understanding of the structure and types of keywords while conducting the search. The results showed that overall the searches were dominated by a few keywords, such as “hotel,” “map,” “information,” “guide,” and “events,” and these keywords could be classified into categories such as accommodation, destination, and information.…”

Section: Related Workmentioning

confidence: 99%

Understanding tourists' collaborative information retrieval behavior to inform design

Arif

Lee

2015

Asso for Info Science & Tech

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With the rapid development of information and communication technologies, people are increasingly referring to web information to assist in their travel planning and decision making. Research shows that people conduct collaborative information searches while planning their travel activities online. However, little is known in depth about tourists' online collaborative search. This study examines tourists' collaborative information search behavior in detail, including their search stages, online search strategies, and information flow breakdowns. The data for analysis included pre‐ and postsearch questionnaires, web search and chat logs, and postsearch interviews. A model of tourist collaborative information retrieval was developed. The model identified collaborative planning, collaborative information searching, sharing of information, and collaborative decision making as four stages of tourists' collaborative search. The results show that tourists collaborated by planning their search strategies, dividing search tasks into subtasks and allocating workload, using search queries and URL links recommended by teammates, and discussing search results together. Related personal knowledge and experiences appeared important in trip planning and collaborative information search. During the collaborative search, tourists also encountered various information flow breakdowns in different search stages. These were classified and their effects on collaborative information search were reported. Implications for system design in support of collaborative information retrieval in travel contexts are also discussed.

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“…Our preliminary study conforms to the study [14] on tourists' search behavior which identifies the most frequently used keywords as: destination (e.g. country, city), hotel, weather, food, travel route, and visa information.…”

Section: Theoretical Modelmentioning

confidence: 92%

“…There is a need for communication and feedback thus allowing for refinement of the information and tour plan. Travelers tend to acquire information through communities [1,14] and these communities comprise networks of people who can exchange information. These might be personal networks like family and workmates, but also wider ones such as participants on the Web.…”

Section: Related Workmentioning

confidence: 99%

Towards a model of collaborative information retrieval in tourism

Arif

Lee

2012

Proceedings of the 4th Information Interaction in Context Symposium

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The research area of collaborative information retrieval (CIR) has received increasing interest from interactive information retrieval researchers in recent years. Various studies on CIR have been conducted within different contexts and illuminated some key aspects of CIR. However, the research area of CIR for tourism is still in its early stages. This paper reports on our ongoing research into the development of a collaborative tourism information retrieval model that combines the processes of tourists' collaboration and information retrieval. Based on prior research and our survey results, a preliminary theoretical model of CIR in tourism domain was developed. The model provides insights for our future design of a collaborative tourism information retrieval system.

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Understanding the Information Search Process within a Tourism Domain-specific Search Engine

Cited by 18 publications

References 18 publications

Travelers' Intent to Use Mobile Technologies as a Function of Effort and Performance Expectancy

Travelers' Intent to Use Mobile Technologies as a Function of Effort and Performance Expectancy

Understanding tourists' collaborative information retrieval behavior to inform design

Towards a model of collaborative information retrieval in tourism

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